Stochastic model of production and inventory control using dynamic bayesian network

Ji Sun Shin*, Tae Hong Lee, Jin Il Kim, Hee Hyol Lee

*この研究の対応する著者

研究成果査読

3 被引用数 (Scopus)

抄録

Bayesian Network is a stochastic model, which shows the qualitative dependence between two or more random variables by the graph structure, and indicates the quantitative relations between individual variables by the conditional probability. This paper deals with the production and inventory control using the dynamic Bayesian network. The probabilistic values of the amount of delivered goods and the production quantities are changed in the real environment, and then the total stock is also changed randomly. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the Bayesian network. Moreover, an adjusting rule of the production quantities to maintain the probability of the lower bound and the upper bound of the total stock to certain values is shown.

本文言語English
ページ(範囲)148-154
ページ数7
ジャーナルArtificial Life and Robotics
13
1
DOI
出版ステータスPublished - 2008 12 1

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 人工知能

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